Run Generation Revisited: What Goes Up May or May Not Come Down

In this paper, we revisit the classic problem of run generation. Run generation is the first phase of external-memory sorting, where the objective is to scan through the data, reorder elements using a small buffer of size M , and output runs (contiguously sorted chunks of elements) that are as long as possible. We develop algorithms for minimizing the total number of runs (or equivalently, maximizing the average run length) when the runs are allowed to be sorted or reverse sorted. We study the problem in the online setting, both with and without resource augmentation, and in the offline setting. (1) We analyze alternating-up-down replacement selection (runs alternate between sorted and reverse sorted), which was studied by Knuth as far back as 1963. We show that this simple policy is asymptotically optimal. Specifically, we show that alternating-up-down replacement selection is 2-competitive and no deterministic online algorithm can perform better. (2) We give online algorithms having smaller competitive ratios with resource augmentation. Specifically, we exhibit a deterministic algorithm that, when given a buffer of size 4M , is able to match or beat any optimal algorithm having a buffer of size M . Furthermore, we present a randomized online algorithm which is 7/4-competitive when given a buffer twice that of the optimal. (3) We demonstrate that performance can also be improved with a small amount of foresight. We give an algorithm, which is 3/2-competitive, with foreknowledge of the next 3M elements of the input stream. For the extreme case where all future elements are known, we design a PTAS for computing the optimal strategy a run generation algorithm must follow. (4) Finally, we present algorithms tailored for nearly sorted inputs which are guaranteed to have optimal solutions with sufficiently long runs

A scheme to aid construction of left-hand sides of axioms in algebraic specifications for object-oriented program testing

In order to ensure reliability and quality, software systems must be tested. Testing object-oriented software is harder than testing procedure-oriented software. It involves four levels, namely the algorithmic level, class level, cluster level, and system level. We proposed a methodology TACCLE for class-and cluster- level testing. It includes an important algorithm GFT for generating fundamental equivalent pairs as class-level test cases based on axioms in a given algebraic specification for a given class. This formal methodology has many benefits. However, system analysts often find it difficult to construct axioms for algebraic specifications. In this paper, we propose a scheme to aid the construction of the left-hand sides of axioms. The scheme alleviates the difficulties of the system analysts and also helps them check the completeness, consistency, and independence of the axiom system. © 2008 IEEE.published_or_final_versionUnion Grant of Guangdong Province and National Natural Science Foundation of China (#U0775001), Guangdong Province Science Foundation (#7010116), and by a grant of the Youth Science Foundation of Jinan University (#51208035)

A predictive continuum dynamic user-optimal model for a polycentric urban city

A predictive continuum dynamic user-optimal model is extended to investigate the traffic equilibrium problem for a polycentric urban city with multiple central business districts (CBDs). The road network within the city is assumed to be dense and can be viewed as a continuum in which travellers can choose their routes in a two-dimensional space. Travellers are assumed to choose their route to minimise the actual total cost to the destination (i.e. the CBD). The model consists of two parts: the conservation law part and the Hamilton–Jacobi part. The finite volume method is used to solve each part on unstructured meshes. Because the two parts are closely interconnected and have different initial times, solving the model can be treated as a fixed-point problem, which is solved using a self-adaptive method of successive averages. Numerical experiments for an urban city with two CBDs are presented to demonstrate the effectiveness of the model and the numerical algorithm.postprin

Mesoscale modeling and simulation of microstructure evolution during dynamic recrystallization of a Ni-based superalloy

Microstructural evolution and plastic flow characteristics of a Ni-based superalloy were investigated using a simulative model that couples the basic metallurgical principle of dynamic recrystallization (DRX) with the twodimensional (2D) cellular automaton (CA). Variation of dislocation density with local strain of deformation is considered for accurate determination of the microstructural evolution during DRX. The grain topography, the grain size and the recrystallized fraction can be well predicted by using the developed CA model, which enables to the establishment of the relationship between the flow stress, dislocation density, recrystallized fraction volume, recrystallized grain size and the thermomechanical parameters

Single channel wireless EEG device for real-time fatigue level detection

© 2015 IEEE. Driver fatigue problem is one of the important factors of traffic accidents. Recent years, many research had investigated that using EEG signals can effectively detect driver's drowsiness level. However, real-time monitoring system is required to apply these fatigue level detection techniques in the practical application, especially in the real-road driving. Therefore, it required less channels, portable and wireless, real-time monitoring and processing techniques for developing the real-time monitoring system. In this study, we develop a single channel wireless EEG device which can real-time detect driver's fatigue level on the mobile device such as smart phone or tablet. The developed device is investigated to obtain a better and precise understanding of brain activities of mental fatigue under driving, which is of great benefit for devolvement of detection of driving fatigue system. This system consists of a Bluetooth-enabled one channel EEG, a regression model, and smartphone, which was a platform recording and transforming the raw EEG data to useful driving status. In the experiment, this was a sustained-attention driving task to implement in a virtual-reality (VR) driving simulator. To training model and develop the system, we were performed for 15 subjects to study Electroencephalography (EEG) brain dynamics by using a mobile and wireless EEG device. Based on the outstanding training results, the leave-one-subject-out cross validation test obtained 90% fatigue detection accuracy. These results indicate that the combination of a smartphone and wireless EEG device constitutes an effective and easy wearable solution for detecting and preventing driver fatigue in real driving environments

Determinants of the creatinine clearance to glomerular filtration rate ratio in patients with chronic kidney disease: a cross-sectional study

BACKGROUND: Creatinine secretion, as quantified by the ratio of creatinine clearance (CrCl) to glomerular filtration rate (GFR), may introduce another source of error when using serum creatinine concentration to estimate GFR. Few studies have examined determinants of the CrCl/GFR ratio. We sought to study whether higher levels of albuminuria would be associated with higher, and being non-Hispanic black with lower, CrCl/GFR ratio. METHODS: We did a cross-sectional analysis of 1342 patients with chronic kidney disease from the Chronic Renal Insufficiency Cohort (CRIC) who had baseline measure of iothalamate GFR (iGFR) and 24-hour urine collections. Our predictors included urine albumin as determined from 24-hour urine collections (categorized as: <30, 30-299, 300-2999 and ≥3000 mg), and race/ethnicity (non-Hispanic white, non-Hispanic black, Hispanic). Our outcome was CrCl/iGFR ratio, a measure of creatinine secretion. RESULTS: Mean iGFR was 48.0 ± 19.9 mL/min/1.73 m(2), median albuminuria was 84 mg per day, and 36.8% of the study participants were non-Hispanic black. Mean CrCl/iGFR ratio was 1.19 ± 0.48. There was no association between the CrCl/iGFR ratio and urine albumin (coefficient 0.11 [95% CI−0.01-0.22] for higest verus lowest levels of albuminuria, p = 0.07). Also, there was no association between race/ethnicity and CrCl/iGFR ratio (coefficient for non-Hispanic blacks was−0.03 [95% CI−0.09-0.03] compared with whites, p = 0.38). CONCLUSIONS: Contrary to what had been suggested by prior smaller studies, CrCl/GFR ratio does not vary with degree of proteinuria or race/ethnicity. The ratio is also closer to 1.0 than reported by several frequently cited reports in the literature

Development of a Bonner Sphere neutron spectrometer from a commercial neutron dosimeter

Bonner Spheres have been used widely for the measurement of neutron spectra with neutron energies ranged from thermal up to at least 20 MeV . A Bonner Sphere neutron spectrometer (BSS) was developed by extending a Berthold LB 6411 neutron-dose-rate meter. The BSS consists of a 3He thermal-neutron detector with integrated electronics, a set of eight polyethylene spherical shells and two optional lead shells of various sizes. The response matrix of the BSS was calculated with GEANT4 Monte Carlo simulation. The BSS had a calibration uncertainty of ± 8.6% and a detector background rate of (1.57 ± 0.04) × 10−3 s−1. A spectral unfolding code NSUGA was developed. The NSUGA code utilizes genetic algorithms and has been shown to perform well in the absence of a priori information.postprin

Flood impact assessment under climate change scenarios in central Taipei area, Taiwan

Providing effective information regarding flood control for responding climate change is essential to future flood risk management for cities. This study simulated and assessed the impacts of flooding for future climate change scenarios in Taipei city, Taiwan. We modelled rainfall events, generated by general circulation models, with different return periods. The flood extents and damage in the Central Taipei Area for the A1B climate change scenarios were compared to the ones, caused by the rainfall events with same return periods, without climate change (baseline scenario). The proposed approach provides potential flooding maps and flood damage assessment for climate change scenarios as useful information for flood risk management in urban areas.The work is supported by the National Science Council, Taiwan (NSC 99-2915-I-002-120) and the CORFU project, funded by the European Commission through Framework Programme 7, Grant Number 244047

Emotional Fuzzy Sliding-Mode Control for Unknown Nonlinear Systems

[[abstract]]The brain emotional learning model can be implemented with a simple hardware and processor; however, the learning model cannot model the qualitative aspects of human knowledge. To solve this problem, a fuzzy-based emotional learning model (FELM) with structure and parameter learning is proposed. The membership functions and fuzzy rules can be learned through the derived learning scheme. Further, an emotional fuzzy sliding-mode control (EFSMC) system, which does not need the plant model, is proposed for unknown nonlinear systems. The EFSMC system is applied to an inverted pendulum and a chaotic synchronization. The simulation results with the use of EFSMC system demonstrate the feasibility of FELM learning procedure. The main contributions of this paper are (1) the FELM varies its structure dynamically with a simple computation; (2) the parameter learning imitates the role of emotions in mammalians brain; (3) by combining the advantage of nonsingular terminal sliding-mode control, the EFSMC system provides very high precision and finite-time control performance; (4) the system analysis is given in the sense of the gradient descent method.[[notice]]補正完